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Changha Hwang
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2020 – today
- 2023
- [i1]Hangbin Lee, Il Do Ha, Changha Hwang, Youngjo Lee:
Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features. CoRR abs/2310.11654 (2023)
2010 – 2019
- 2018
- [j25]Masoud Reyhani Hamedani
, Dongjin Shin
AndroClass: An Effective Method to Classify Android Applications by Applying Deep Neural Networks to Comprehensive Features. Wirel. Commun. Mob. Comput. 2018: 1250359:1-1250359:21 (2018) - 2017
- [j24]Jooyong Shim, Insuk Sohn, Changha Hwang:
Kernel-based random effect time-varying coefficient model for longitudinal data. Neurocomputing 267: 500-507 (2017) - [j23]Jooyong Shim, Changha Hwang:
Kernel-based orthogonal quantile regression model. Model. Assist. Stat. Appl. 12(3): 217-226 (2017) - 2016
- [j22]Jooyong Shim, Changha Hwang, Kyung Ha Seok:
Support vector quantile regression with varying coefficients. Comput. Stat. 31(3): 1015-1030 (2016) - 2015
- [j21]Jooyong Shim, Changha Hwang:
Varying coefficient modeling via least squares support vector regression. Neurocomputing 161: 254-259 (2015) - 2014
- [j20]Jooyong Shim, Changha Hwang, Kyung Ha Seok:
Composite support vector quantile regression estimation. Comput. Stat. 29(6): 1651-1665 (2014) - [j19]Jooyong Shim, Okmyung Bin, Changha Hwang:
Semiparametric spatial effects kernel minimum squared error model for predicting housing sales prices. Neurocomputing 124: 81-88 (2014) - [j18]Jooyong Shim, Changha Hwang:
Estimating small area mean with mixed and fixed effects support vector median regressions. Neurocomputing 145: 174-181 (2014) - 2012
- [j17]Jooyong Shim, Yongtae Kim, Jangtaek Lee, Changha Hwang:
Estimating value at risk with semiparametric support vector quantile regression. Comput. Stat. 27(4): 685-700 (2012) - 2011
- [j16]Kyung Ha Seok, Jooyong Shim, Daehyeon Cho, Gyu-Jeong Noh, Changha Hwang:
Semiparametric mixed-effect least squares support vector machine for analyzing pharmacokinetic and pharmacodynamic data. Neurocomputing 74(17): 3412-3419 (2011)
2000 – 2009
- 2009
- [j15]Jooyong Shim, Changha Hwang:
Support vector censored quantile regression under random censoring. Comput. Stat. Data Anal. 53(4): 912-919 (2009) - [j14]Insuk Sohn, Jooyong Shim, Changha Hwang, Sujong Kim, Jae Won Lee:
Informative transcription factor selection using support vector machine-based generalized approximate cross validation criteria. Comput. Stat. Data Anal. 53(5): 1727-1735 (2009) - [j13]Jooyong Shim, Insuk Sohn, Sujong Kim, Jae Won Lee, Paul E. Green, Changha Hwang:
Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine. Comput. Stat. Data Anal. 53(5): 1736-1742 (2009) - [j12]Jooyong Shim, Changha Hwang, Kyung Ha Seok:
Non-crossing quantile regression via doubly penalized kernel machine. Comput. Stat. 24(1): 83-94 (2009) - 2008
- [j11]Insuk Sohn, Sujong Kim, Changha Hwang, Jae Won Lee:
New normalization methods using support vector machine quantile regression approach in microarray analysis. Comput. Stat. Data Anal. 52(8): 4104-4115 (2008) - 2007
- [j10]Dug Hun Hong, Changha Hwang, Kyung Tae Kim:
T-sum of sigmoid-shaped fuzzy intervals. Inf. Sci. 177(18): 3831-3839 (2007) - 2006
- [j9]Changha Hwang, Dug Hun Hong, Kyung Ha Seok:
Support vector interval regression machine for crisp input and output data. Fuzzy Sets Syst. 157(8): 1114-1125 (2006) - [c10]Dug Hun Hong, Changha Hwang, Jooyong Shim, Kyung Ha Seok:
Locally Weighted LS-SVM for Fuzzy Nonlinear Regression with Fuzzy Input-Output. CIS 2006: 317-325 - [c9]Dug Hun Hong, Changha Hwang:
Fuzzy Nonlinear Regression Model Based on LS-SVM in Feature Space. FSKD 2006: 208-216 - [c8]Jooyong Shim, Changha Hwang, Sungkyun Nau:
Robust LS-SVM Regression Using Fuzzy C-Means Clustering. ICNC (1) 2006: 157-166 - 2005
- [j8]Changha Hwang, Dug Hun Hong:
Analyzing the Nonlinear Time Series of Turbulent Flows with Kernel Interval Regression Machine. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 13(4): 365-380 (2005) - [j7]Dug Hun Hong, Changha Hwang:
Interval regression analysis using quadratic loss support vector machine. IEEE Trans. Fuzzy Syst. 13(2): 229-237 (2005) - [c7]Changha Hwang, Dug Hun Hong, Eunyoung Na, Hyejung Park, Jooyong Shim:
Interval Regression Analysis Using Support Vector Machine and Quantile Regression. FSKD (1) 2005: 100-109 - [c6]Changha Hwang, David K. Y. Chiu, Insuk Sohn:
Exon Structure Analysis via PCA and ICA of Short-Time Fourier Transform. ICNC (2) 2005: 306-315 - [c5]Changha Hwang, Jooyong Shim:
A Simple Quantile Regression via Support Vector Machine. ICNC (1) 2005: 512-520 - [c4]Jooyong Shim, Changha Hwang:
Doubly Regularized Kernel Regression with Heteroscedastic Censored Data. ICNC (1) 2005: 521-527 - [c3]Changha Hwang, Kyung Ha Seok, Daehyeon Cho:
A Prediction Interval Estimation Method for KMSE. ICNC (1) 2005: 536-545 - 2004
- [j6]Tae Yoon Kim, Kyong Joo Oh, Insuk Sohn, Changha Hwang:
Usefulness of artificial neural networks for early warning system of economic crisis. Expert Syst. Appl. 26(4): 583-590 (2004) - [j5]Dug Hun Hong, Changha Hwang, Chulhwan Ahn:
Ridge estimation for regression models with crisp inputs and Gaussian fuzzy output. Fuzzy Sets Syst. 142(2): 307-319 (2004) - [j4]Dug Hun Hong, Changha Hwang:
Ridge Regression Procedures For Fuzzy Models Using Triangular Fuzzy Numbers. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 12(2): 145-160 (2004) - [j3]Dug Hun Hong, Changha Hwang:
Extended fuzzy regression models using regularization method. Inf. Sci. 164(1-4): 31-46 (2004) - 2003
- [j2]Dug Hun Hong, Changha Hwang:
Support vector fuzzy regression machines. Fuzzy Sets Syst. 138(2): 271-281 (2003) - [c2]Byung-Joo Kim, Jooyong Shim, Changha Hwang, Il Kon Kim, Joon Hyun Song:
Incremental Feature Extraction Based on Empirical Kernel Map. ISMIS 2003: 440-444 - 2002
- [c1]Dug Hun Hong, Changha Hwang:
Extended Fuzzy Regression Models. JCIS 2002: 304-308
1990 – 1999
- 1997
- [j1]Dug Hun Hong, Changha Hwang:
A T-sum bound of LR-fuzzy numbers. Fuzzy Sets Syst. 91(2): 239-252 (1997)
Coauthor Index
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